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Performancemodeling of a geophysics application to accelerate over-decomposition parameter tuning through simulation

机译:地球物理应用程序的性能建模,可通过仿真来加速过度分解参数的调整

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Finite-difference methods are commonplace in High Performance Computing applications. Despite their apparent regularity, they often exhibit load imbalance that damages their efficiency. We characterize the spatial and temporal load imbalance ofOndes3D, a typical finite-differences application dedicated to earthquake modeling. Our analysis reveals imbalance originating from the structure of the input data, and from low-level CPU optimizations. Ondes3D was successfully ported to AMPI/CHARM++ using over-decomposition and MPI process migration techniques to dynamically rebalance the load. However, this approach requires careful selection of the over-decomposition level, the load balancing algorithm, and its activation frequency. These choices are usually tied to application structure and platform characteristics. In this article, we propose a workflow that leverages the capabilities of SimGrid to conduct such study at low experimental cost. We rely on a combination of emulation, simulation, and application modeling that requires minimal codemodification and manages to capture both spatial and temporal load imbalance to faithfully predict the performance of dynamic load balancing.We evaluate the quality of our simulation by comparing simulation results with the outcome of real executions and demonstrate how this approach can be used to quickly find the optimal load balancing configuration for a given application/hardware configuration.
机译:有限差分方法在高性能计算应用程序中很常见。尽管它们具有明显的规律性,但它们经常会出现负载不平衡的情况,从而损害其效率。我们表征了Ondes3D的空间和时间负载不平衡,这是专门用于地震建模的典型有限差分应用程序。我们的分析揭示了输入数据结构和低级CPU优化引起的不平衡。 Ondes3D已使用过度分解和MPI流程迁移技术成功地移植到AMPI / CHARM ++,以动态地重新平衡负载。但是,此方法需要仔细选择过度分解级别,负载平衡算法及其激活频率。这些选择通常与应用程序结构和平台特性有关。在本文中,我们提出了一种工作流,该工作流利用SimGrid的功能以较低的实验成本进行此类研究。我们依赖于仿真,仿真和应用程序建模的组合,这些组合需要最少的代码修改,并能够捕获空间和时间上的负载不平衡,从而忠实地预测动态负载平衡的性能。实际执行的结果,并演示如何使用此方法快速找到给定应用程序/硬件配置的最佳负载平衡配置。

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